The rate of conversion of cloud droplets to precipitation, known as the autoconversion rate, remains a major source of uncertainty in characterizing aerosol’s cloud lifetime effects and precipitation in global and regional models.
To assess the impact of observation period and gauge location, model parameters were learned on scenarios using different chunks of streamflow observations.
This study presents an automated method to detect and classify open- and closed-cell mesoscale cellular convection (MCC) using long-term ground-based radar observations.
EZBattery Model allows energy storage researchers to more quickly and easily identify the best performing battery designs without the need for extensive physical prototyping or computationally expensive simulations.
Sergei Kalinin, a joint appointee at the University of Tennessee, Knoxville and PNNL, and Ji-Guang (Jason) Zhang, a PNNL Lab Fellow, are part of the 2024 class of National Academy of Inventors Fellows.
A paper published last year by scientists at Pacific Northwest National Laboratory was featured in the 2021 Editor’s Choice collection for the Cell Reports Physical Science journal.
As he prepares to enter PNNL's Energy Sciences Center later this year, Vijayakumar 'Vijay' Murugesan is among DOE leaders exploring solutions to design and build transformative materials for batteries of the future.
Scientists have created a single-crystal, nickel-rich cathode that is hardier and more efficient than before—important progress on the road to better lithium-ion batteries for electric vehicles.
